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How to Utilize My App Reviews? A Novel Topics Extraction Machine Learning Schema for Strategic Business Purposes.

Ioannis Triantafyllou1, Ioannis C Drivas1, Georgios Giannakopoulos1

  • 1Research Lab of Information Management, Department of Archival, Library Science and Information Studies, University of West Attica, Ag. Spyridonos, Egaleo, 12243 Athens, Greece.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
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Sensors (Basel, Switzerland)·2024
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This study introduces a new method for classifying app reviews, improving software development and marketing. The DEVMAX.DF feature extraction method effectively identifies key terms for better app insights.

Area of Science:

  • Computer Science
  • Data Science
  • Software Engineering

Background:

  • Understanding user opinions from app reviews is crucial for app improvement and strategic marketing.
  • Classifying app reviews into specific topics is complex, requiring advanced text processing and machine learning.

Purpose of the Study:

  • To propose a novel feature engineering classification schema for efficient app review topic identification.
  • To introduce a new feature extraction method, DEVMAX.DF, for enhanced app review analysis.

Main Methods:

  • Developed a novel feature engineering classification schema.
  • Implemented a new feature extraction method: DEVMAX.DF.
  • Utilized machine learning algorithms for classification and validated through simulations.
Keywords:
app business strategyapp reviewsfeature extraction methodsmachine learning methodsreviews classificationtext analysistext classificationtopics extraction

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Main Results:

  • The proposed DEVMAX.DF schema outperforms traditional methods like TF.IDF and χ² in classifying app reviews.
  • The schema enables earlier and more efficient identification of relevant terms within reviews.

Conclusions:

  • The DEVMAX.DF schema offers a more effective solution for app review classification problems.
  • This research enhances decision-making for practitioners and researchers in app review utilization.